Live opening · Posted 3 days ago
RAG Engineer
Nebulai · United States (Remote)
You are 3 days behind. JobBeeper subscribers saw this role while it was still new.
At a glance
The key details from the original listing.
CompanyNebulai
LocationUnited States (Remote)
Work modeYes
Source
Linkedin
Listed3 days ago
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About the role
Description supplied by the original job listing.
Sweat chunking, retrieval quality, and citations—not just we added a vector DB.”
Through Nebulai’s marketplace, you embed with client teams building retrieval-augmented systems that answer from their docs and systems of record: ingest pipelines, hybrid search, reranking, grounding checks, and the eval loop that proves its getting better. Practical delivery. Accountable quality. Escape the pilot trap.
Strong fit if you:
- Have shipped production RAG (embeddings, chunking, hybrid search, rerankers)
- Are solid in Python and know at least one vector/search stack
- Measure recall@k, faithfulness, and user-visible failure modes
- Work well with data owners and security on access control for retrieved content
Bonus if you’ve:
- Built multi-corpus or permission-aware retrieval
- Combined RAG with agents/tool calling
- Tuned latency/cost without tanking answer quality
Apply at https://nebulai.app
Work arrangement
Yes
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